DIME / ITDG Meeting Luxemburg, 14 Feb 2017 Smart Statistics DIME / ITDG Meeting Luxemburg, 14 Feb 2017

In the era of real-time algorithmic decision making What is the place of Official Statistics? Issues? Challenges? Opportunities? Responsibilities?......?

From Big Data to Smart Statistics Leveraging work on big data to develop cognitive statistics with algorithmic intelligence, automation, new standards, methods, ….., to meet the data4policy needs in a highly digital world

…transiting into Smart Statistics… this job is Nearly Impossible Challenging Questionable …….but also….. Fascinating Inspiring Innovative Motivating Technically Statistically Ethically Legally Intellectually Practically ……. Necessary and Possible

New, dynamic data ecosystems Massive increase of data production and exchange Not manageable by humans Exchange of data without human intervention Autonomous Agents Filtering, aggregation Decisions Cognitive systems Can we use this new internet for producing statistics in an intelligent way?

Big Data Most if not all data in a decade will be "organic"

Internet of Things / Wearable Internet Sensors Internet of Things / Wearable Internet Machines communicate with machines and humans Massive exchange of data & information Intelligent systems to extract and aggregate data and transform to information IoT will affect private life and economy Intelligent home Intelligent cities Industry 4.0 Systems will take(semi)autonomous decisions

In order to realise the full benefits of AI, ‘things need to be connected first’

Artificial Intelligence & Machine Learning

The Cloud is a key component in Datafication

Internet of Things - Networks https://opentechdiary.wordpress.com/tag/internet-of-things/

Smart Statistics We can think of Smart Statistics as being the future system of official statistics, where data capturing, processing and analysis will be embedded in the system itself, starting with the digital footprints of the activity. putting intelligence to all stages of the data lifecycle it is expected to enhance the efficiency of the entire statistical system and enable the ESS to maintain and reinforce its role as a key provider of data4policy in a digital world

Smart Statistics - Approach Dimensions Architecture What data is where? Where is intelligence put? Owner / operator 3rd party system, system deployed by statistical offices Interactions Between architecture, application domains, policy areas Infrastructure for multiple purposes Blending of traditional sources with smart statistics

Smart Statistics Analysis of Architecture

Smart Systems Application Domain mobility cities homes wearables energy grids manufacturing farming …

Smart Statistics4Policy EU priorities Jobs, Growth and Investment Digital Single Market Energy Union and Climate Internal Market A Deeper and Fairer Economic and Monetary Union Migration A Stronger Global Actor Democratic change

Smart Statistics Contractor's proposal Deliverables Potential policy areas, application domains, cross cutting issues (standards, software, networks, security, confidentiality, quality, methodology, …) Deliverables Use cases definition Literature study as input 3 policy relevant use cases, small scale pilot Generalize stat issues Wider debate among stakeholders Validate use case Proof of concept with small scale piloting Input to large scale piloting Technical workshops

Smart Statistics: What next? Planned Activities Discussions with stakeholders (researchers, industry, …) on future Internet of Things Feasibility Study 2017 Proof of Concept Session in ISI World Statistics Congress 2017 More studies on selected use cases 2018+

Smart Statistics: Discussion What are the basic components of a system(s) of smart statistics? Which are the major statistical issues to address? How should a 'Proof of Concept' look like in practice? Do we need to develop new data and metadata standards together with IoT Standardisation bodies like ETSI? Should we think of 'privacy by design' already at the development of a POC? Whom we should partner with in this path towards smart statistics? What could be the preferred scenario for implementation? Do smart statistics represent new opportunities and challenges for citizen science and citizen data? Can you propose some promising use cases for experimentation of smart statistics? What are the most likely statistical domains for experimentation?

Building a European Data Economy Communication adopted on 10 January 2017 Address issues on free flow of data Emerging legal issues in context of new data technologies access to and transfer of non-personal machine-generated data, data liability, and portability of non-personal data, interoperability and standards. https://ec.europa.eu/digital-single-market/en/news/communication-building-european-data-economy

Building a European Data Economy Access for public interest and scientific purposes Public authorities could be granted access to data where this would be in the "general interest" and would considerably improve the functioning of the public sector … EU needs a policy framework that enables data to be used throughout the value chain for scientific, societal and industrial purposes. To this end, the Commission is launching a wide-ranging stakeholder dialogue on the issues explored in this Communication. The first step in this dialogue will be a public consultation.

Building a European Data Economy Use of commercially held data for official statistics Re-use of smart meter information Job vacancy statistics Anonymised data from mobile phone operators Ways forward Non-legislative approaches Guidance on incentivising business to share data Fostering the development of technical solutions for reliable identification, exchange of, and differentiated access to data Model contract terms Legislative approaches Default contractual rules Access for public interest purposes Data producer's right for non-personal or anonymised data Access against remuneration to non-personal or anonymised data

Building a European Data Economy Public Consultation 10 January – 26 April 2017 1) Localisation of data for storage and / or processing purposes 2) Access to and re-use of non-personal data 3) Liability 4) Portability of non-personal data, interoperability and standards https://ec.europa.eu/digital-single-market/en/news/public-consultation-building-european-data-economy